Gemini 1.0 Pro vs Qwen2.5-Coder 32B Instruct
Qwen2.5-Coder 32B Instruct leads the LLM Stats Score 2.7 to -4.8. Qwen2.5-Coder 32B Instruct is 8.3x cheaper per token.
Google · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen2.5-Coder 32B Instruct leads the overall LLM Stats Score 2.7 to -4.8, ranking #295 overall.
In the 2 individual benchmarks reported for both models, Qwen2.5-Coder 32B Instruct wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen2.5-Coder 32B Instruct is roughly 8.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen2.5-Coder 32B Instruct also accepts a larger context window (128,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Gemini 1.0 Pro
- you want predictable pricing at $0.50/M input and $1.50/M output
Choose Qwen2.5-Coder 32B Instruct
- overall performance matters — it scores 2.7 and ranks #295 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- cost matters — it's about 8.3x cheaper per token
- you process long inputs — it offers a 128,000 token context window
- you want the most recent training data — it shipped Sep 2024
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
9 reported for Gemini 1.0 Pro · 15 for Qwen2.5-Coder 32B Instruct
Gemini 1.0 Pro outperforms in 0 benchmarks, while Qwen2.5-Coder 32B Instruct is better at 2 benchmarks (MATH, MMLU).
Qwen2.5-Coder 32B Instruct significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 1.0 Pro ($0.50/1M tokens) is 5.6x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).
For output processing, Gemini 1.0 Pro ($1.50/1M tokens) is 16.7x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).
In conclusion, Gemini 1.0 Pro is more expensive than Qwen2.5-Coder 32B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Qwen2.5-Coder 32B Instruct accepts 128,000 input tokens compared to Gemini 1.0 Pro's 32,760 tokens. Qwen2.5-Coder 32B Instruct can generate longer responses up to 128,000 tokens, while Gemini 1.0 Pro is limited to 8,192 tokens.
License
Usage and distribution terms
Gemini 1.0 Pro is licensed under a proprietary license, while Qwen2.5-Coder 32B Instruct uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
Gemini 1.0 Pro was released on 2024-02-15, while Qwen2.5-Coder 32B Instruct was released on 2024-09-19.
Qwen2.5-Coder 32B Instruct is 7 months newer than Gemini 1.0 Pro.
Feb 15, 2024
2.5 years ago
Sep 19, 2024
1.9 years ago
7mo newerKnowledge Cutoff
When training data ends
Gemini 1.0 Pro has a documented knowledge cutoff of 2024-02-01, while Qwen2.5-Coder 32B Instruct's cutoff date is not specified.
We can confirm Gemini 1.0 Pro's training data extends to 2024-02-01, but cannot make a direct comparison without Qwen2.5-Coder 32B Instruct's cutoff date.
Feb 2024
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Provider Availability
Gemini 1.0 Pro is available from Google. Qwen2.5-Coder 32B Instruct is available from Lambda, DeepInfra, Hyperbolic, Fireworks.
Gemini 1.0 Pro
Qwen2.5-Coder 32B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 1.0 Pro and Qwen2.5-Coder 32B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 1.0 Pro vs Qwen2.5-Coder 32B Instruct.